Jens Schreiber

Address University of Kassel
Intelligent Embedded Systems
Wilhelmshöher Allee 73
34121 Kassel
Room 0306
Telephone +49 561 804 6469

[2020] [2019] [2018]

2020 [to top]

  • Henze, J., Schreiber, J., Sick, B.: Representation Learning in Power Time Series Forecasting. In: Pedrycz, W. and Chen, S.-M. (eds.) Deep Learning: Algorithms and Applications. p. 67--101. Springer International Publishing (2020).

2019 [to top]

  • Schreiber, J., Buschin, A., Sick, B.: Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models. In: David, K., Geihs, K., Lange, M., and Stumme, G. (eds.) INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik -- Informatik für Gesellschaft. p. 585--598. Gesellschaft für Informatik e.V., Bonn (2019).
  • Schreiber, J., Jessulat, M., Sick, B.: Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic. In: Tetko, I.V., Kurková, V., Karpov, P., and Theis, F. (eds.) Artificial Neural Networks and Machine Learning -- ICANN 2019: Image Processing. p. 550--564. Springer International Publishing, Cham (2019).
  • Schreiber, J.: Transfer Learning in the Field of Renewable Energies -- A Transfer Learning Framework Providing Power Forecasts Throughout the Lifecycle of Wind Farms After Initial Connection to the Electrical Grid. In: Tomforde, S. and Sick, B. (eds.) Organic Computing -- Doctoral Dissertation Colloquium 2018. p. 75--87. Kassel university press (2019).

2018 [to top]

  • Deist, S., Bieshaar, M., Schreiber, J., Gensler, A., Sick, B.: Coopetitive Soft Gating Ensemble. Workshop on Self-Improving System Integration (SISSY). , Trento, Italy (2018).
  • Schreiber, J., Sick, B.: Quantifying the Influences on Probabilistic Wind Power Forecasts. International Conference on Power and Renewable Energy. p. 6 (2018).